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All-electron machine-learned orbital-free density functional for periodic CHNO systems
Marc K. Ickler, Andreas Hermann, Fred A. Hamprecht
We introduce STRUCTURES-P, a machine-learned all-electron orbital-free density functional for periodic CHNO systems. Electrostatics are evaluated analytically in an atom-centered G…
Orbital-Free Surrogate Functionals Yield Transferable Interatomic Potentials and Electron Densities
Simon Wagner, Marc K. Ickler, Manuel V. Klockow +2
Orbital-free density functional theory seeks to compute the energy of an electronic system directly from its electron density, avoiding one-electron wave functions and thereby offe…
Rotational Equivariance in Machine Learning: A Comprehensive Tutorial
Peter Lippmann, Fred A. Hamprecht
Rotational symmetry is one of the most important structural principles in machine learning on 3D data. In applications ranging from physics and materials science to 3D computer vis…
Surrogate Functionals for Machine-Learned Orbital-Free Density Functional Theory
Roman Remme, Fred A. Hamprecht
We introduce surrogate functionals: machine-learned energy functionals for orbital-free density functional theory (OF-DFT) which are defined not by universal fidelity to a physical…